Lower quartile (25th percentile) and lower quintile (20th percentile) gross and disposable (after tax) household income. By Regional Council. Timeseries: Years ending June 2007 – 2020 Source: Stats NZ Household Economic Survey Source: Stats NZ Censuses of Population and Dwellings

Note: In these datasets, a person is defined as up to date if they have received at least one dose of an updated COVID-19 vaccine. The Centers for Disease Control and Prevention (CDC) recommends that certain groups, including adults ages 65 years and older, receive additional doses.

Starting on July 13, 2022, the denominator for calculating vaccine coverage has been changed from age 5+ to all ages to reflect new vaccine eligibility criteria. Previously the denominator was changed from age 16+ to age 12+ on May 18, 2021, then changed from age 12+ to age 5+ on November 10, 2021, to reflect previous changes in vaccine eligibility criteria. The previous datasets based on age 12+ and age 5+ denominators have been uploaded as archived tables.

Starting June 30, 2021, the dataset has been reconfigured so that all updates are appended to one dataset to make it easier for API and other interfaces. In addition, historical data has been extended back to January 5, 2021.

This dataset shows full, partial, and at least 1 dose coverage rates by zip code tabulation area (ZCTA) for the state of California. Data sources include the California Immunization Registry and the American Community Survey’s 2015-2019 5-Year data.

This is the data table for the LHJ Vaccine Equity Performance dashboard. However, this data table also includes ZTCAs that do not have a VEM score.

This dataset also includes Vaccine Equity Metric score quartiles (when applicable), which combine the Public Health Alliance of Southern California’s Healthy Places Index (HPI) measure with CDPH-derived scores to estimate factors that impact health, like income, education, and access to health care. ZTCAs range from less healthy community conditions in Quartile 1 to more healthy community conditions in Quartile 4.

The Vaccine Equity Metric is for weekly vaccination allocation and reporting purposes only. CDPH-derived quartiles should not be considered as indicative of the HPI score for these zip codes. CDPH-derived quartiles were assigned to zip codes excluded from the HPI score produced by the Public Health Alliance of Southern California due to concerns with statistical reliability and validity in populations smaller than 1,500 or where more than 50% of the population resides in a group setting.

These data do not include doses administered by the following federal agencies who received vaccine allocated directly from CDC: Indian Health Service, Veterans Health Administration, Department of Defense, and the Federal Bureau of Prisons.

For some ZTCAs, vaccination coverage may exceed 100%. This may be a result of many people from outside the county coming to that ZTCA to get their vaccine and providers reporting the county of administration as the county of residence, and/or the DOF estimates of the population in that ZTCA are too low. Please note that population numbers provided by DOF are projections and so may not be accurate, especially given unprecedented shifts in population as a result of the pandemic.

Last Version: 3

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/10/28

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers.
File list:

- data_articles_journal_list_v3.xlsx: full list of 124 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_3.csv: full list of 124 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 3rd version
- Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types
- Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Journal Citation Reports (JCR) and/or Scimago Journal and Country Rank (SJR).

Erratum - Data articles in journals Version 3:

Botanical Studies -- ISSN 1999-3110 -- JCR (JIF) Q2
Data -- ISSN 2306-5729 -- JCR (JIF) n/a
Data in Brief -- ISSN 2352-3409 -- JCR (JIF) n/a

Version: 2

Author: Francisco Rubio, Universitat Politècnia de València.

Date of data collection: 2020/06/23

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers.
File list:

- data_articles_journal_list_v2.xlsx: full list of 56 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_v2.csv: full list of 56 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 2nd version
- Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types
- Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Scimago Journal and Country Rank (SJR)

Total size: 32 KB

Version 1: Description

This dataset contains a list of journals that publish data articles, code, software articles and database articles.

The search strategy in DOAJ and Ulrichsweb was the search for the word data in the title of the journals.
Acknowledgements:
Xaquín Lores Torres for his invaluable help in preparing this dataset.

Median, lower quartile, upper quartile statistics for: • Household income for renters • Rental payments By region (Regional Council, Territorial Authority, Auckland local board) and sector of landlord and household composition. Timeseries: 2001, 2006, 2013, 2018 Source: Stats NZ Censuses of Population and Dwellings

Financial ratios of farms, by farm type and quartile boundary, incorporated and unincorporated sectors, Canada. Data are available on an annual basis.

Data source

Taken from chapter 5 of Machine learning cookbook for cyber security

Data dictionary

number in brackets states the number of described features

"..." - stands for multiple optional names that match the given pattern

.

..._ip, ..._port

(4): IP and port of client / srver

packets_...

(3): Number of packets sent by client / server / both

ack_...

(3): Number of ACK packets sent by client / server / both

packets_A_B_ratio

(1): Ratio between packets sent by client and sent by server

asn_...

(2): Number of autonomous systems served as client, server

push_...

(3): Number of packets with PSH flag sent by client / server / both

bytes_...

(3): Number of bytes sent by client / server / both

reset_...

(3): Number of packets with RST flag sent by client / server / both

bytes_A_B_ratio

(1): Ratio between number of bytes sent and number of bytes received

ssl_count_certificates

(1): Number of SSL certificates

cap_date

(1): date of data capturing start

ssl_count_client_...

(6): Client: Number of supported SSL cipher algorithms / ciphersuites / compressions / eliptic curves / key exchange algorithms / MAC algorithms

country_...

(2): Number of countries systems served as client / server

ssl_count_server_...

(6): Server: Number of supported SSL cipher algorithms / ciphersuites / compressions / eliptic curves / key exchange algorithms / MAC algorithms

daysTime

(1): When during the day communication was established

ssl_dom_server_ciphersuite

(1): Number of SSL versions

dns_alexaRank

(1): DNS response server Alexa rank

ssl_dom_server_compression

(5): Dominated SSL ciphersuite / eliptic curve / server name / server rank / version

dns_count_addresses

(4): Number of adresses / answer / authoritative / additional fields in DNS response

ssl_handshake_duration_...

(10): SSL handshake duration: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

dns_count_canon_names

(1): Number of canonical names in DNS response

ssl_ratio_...

(7): Ratio between ssl sessions and: expired certificates / client cipher algorithms / ciphersuits / eliptic curves / client key exchange algorithms / client MAC algorithms / server names

dns_flag

(1): DNS response flags combinations

ssl_req_bytes_...

(10): Number of request bytes: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

dns_host_name

(1): DNS host name

ssl_resp_bytes_...

(10): Number of response bytes: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

dns_min_ttl

(1): DNS response minimal time-to-live

start

(1): session start (date-time)

dns_pre_bad_requests

(1): Number of preceding bad DNS responses

tcp_analysis_...

(6): TCP: Number of packets with Keep Alive packets / lost segments / packets received out of order / retransmitted packets / reused ports / duplicake ACKs

dns_time

(1): Time took to receive DNS response

ttl_A_...

(10): TCP packet time-to-live sent by client: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

ds_field_...

(2): Differentiated Services (DS) field sent by client / server

ttl_...

(10): TCP packet time-to-live: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

duration

(1): Session duration

ttl_B_...

(10): TCP packet time-to-live sent by server: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

http_bytes_...

(10): Number of bytes sent by client over HTTP: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy.

urg_...

(3): Packets with URG flag sent by client / server / both

http_cookie_count

(1): Total number of cookie values

weekDay

(1): day of week (Sunday, Monday, …)

http_cookie_values_...

(10): Number of cookie values: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

domain / subdomain / suffix

(3): Dminated host's URL: domain / subdomain / suffix

http_count_...

(6): HTTP: Number of hosts / unique content types used in request / unique response codes / unique response content types / transactions / unique user agents

is_ad_http

(1): subdomain of HTTP dominated host includes ad-related keywords

http_dom_...

(8): Dominated HTTP: browser / browser version / host / host Alexa rank / operating system / operating system version / request contetn type / response code / response contetn type /

is_cdn_http

(1): subdomain of HTTP dominated host includes CDN-related keywords

http_dom_is_bot

(1): Is most of HTTP connections created by known bot

is_cloud_http

(1): subdomain of HTTP dominated host includes cloud-related keywords

http_GET

(1): Number of HTTP requests submited with GET method

is_...

(3): session protocol is DNS / HTTP / SSL

http_has_...

(4): Does HTTP request have a location / referrer / content type / user agent field

is_g_http

(1): subdomain of HTTP dominated host includes g-related keywords

http_has_resp_content_type

(1): Does HTTP response have a content type field

is_img_http

(1): subdomain of HTTP dominated host includes image-related keywords

http_inter_arrivel_...

(10): HTTP request-response inter arrival time: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

is_m_http

(1): subdomain of HTTP dominated host includes mobile-related keywords

http_POST

(1): Number of HTTP requests submited with POST method

is_maker_site_http

(1): subdomain of HTTP dominated host is of a maker's site

http_req_bytes_...

(10): HTTP request bytes: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

is_media_http

(1): subdomain of HTTP dominated host includes media-related keywords

http_resp_bytes_...

(10): HTTP response bytes: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

is_numeric_url_http

(1): subdomain of HTTP dominated host is numeric

http_time_...

(10): Time took to HTTP server to return response: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

is_numeric_url_with_port_http

(1): subdomain of HTTP dominated host is numeric plus port name

label

(1): malware label

is_tv_http

(1): HTTP dominated host has TV-related keywords

labelSS

(1): malware label

B_is_system_port

(1): destination port is in the range of [1, 1023]

packet_inter_arrivel_A_...

(10): Client packets inter arival time: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

B_is_user_port

(1): destination port is in the range of [1024, 49151]

packet_inter_arrivel_...

(10): Packets inter arival time: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

B_is_dynamic_and_or_private_port

(1): destination port is in the range of [49152, 65535]

packet_inter_arrivel_B_...

(10): Server packets inter arival time: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

B_port_is_...

(10): Destination port is one of recent top 10 most frequent: 80, 23, etc.

packet_size_A_...

(10): Client packets size: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

subdomain_is_...

(10): subdomain of HTTP dominated host is one of recent top 10 most frequent

packet_size_...

(10): Packets size: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

domain_is_...

(10): domain of HTTP dominated host is one of recent top 10 most frequent

packet_size_B_...

(10): Server packets size: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

suffix_is_...

(4): suffix of HTTP dominated host is one of recent top 4most frequent: com, net, etc.

ΔHRexercise: difference between heart-rate at peak exercise and resting heart-rateΔHRrecovery: difference between heart-rate at peak exercise and after 1 min recoveryΔHR5year: difference between resting heart-rate recorded at year 5 and at baseline§The analysis is restricted to 5139 subjects, see methodsRelative risk that was associated with a heart-rate measurement is given for the second, third and fourth quartile, taken the first quartile as reference. Relative risks were estimated with the Cox proportional-hazard model. CI denotes confidence interval.Symbols of p-values for trend test: ***: p

TEM = technical error of measurement; %TEM = relative TEM.

Canadian Internet use survey, household access to the Internet at home, by household income quartile for Canada and provinces from 2010 and 2012.

Percentage of Internet users by selected Internet service and technology, such as; home Internet access, use of smart home devices, use of smartphones, use of social networking accounts, use or purchase of streaming services, use of government services online and online shopping.

Parameters are shown separately for the three different datasets (1, 2, pathological gamblers [PG]).

In 2020, 59 percent of high school graduates from families in the lowest income quartile in the United States enrolled in college. This was a decrease of one percent from the previous year.

This dataset includes one dataset which was custom ordered from Statistics Canada.The table includes information on housing suitability and shelter-cost-to-income ratio by number of bedrooms, housing tenure, status of primary household maintainer, household type, and income quartile ranges for census subdivisions in British Columbia. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and variables: Geography: Non-reserve CSDs in British Columbia - 299 geographies The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. All the geographies requested for this tabulation have been cleared for the release of income data and have a GNR under 50%. Housing Tenure Including Presence of Mortgage (5) 1. Total – Private non-band non-farm off-reserve households with an income greater than zero by housing tenure 2. Households who own 3. With a mortgage1 4. Without a mortgage 5. Households who rent Note: 1) Presence of mortgage - Refers to whether the owner households reported mortgage or loan payments for their dwelling. 2015 Before-tax Household Income Quartile Ranges (5) 1. Total – Private households by quartile ranges1, 2, 3 2. Count of households under or at quartile 1 3. Count of households between quartile 1 and quartile 2 (median) (including at quartile 2) 4. Count of households between quartile 2 (median) and quartile 3 (including at quartile 3) 5. Count of households over quartile 3 Notes: 1) A private household will be assigned to a quartile range depending on its CSD-level location and depending on its tenure (owned and rented). Quartile ranges for owned households in a specific CSD are delimited by the 2015 before-tax income quartiles of owned households with an income greater than zero and residing in non-farm off-reserve dwellings in that CSD. Quartile ranges for rented households in a specific CSD are delimited by the 2015 before-tax income quartiles of rented households with an income greater than zero and residing in non-farm off-reserve dwellings in that CSD. 2) For the income quartiles dollar values (the delimiters) please refer to Table 1. 3) Quartiles 1 to 3 are suppressed if the number of actual records used in the calculation (not rounded or weighted) is less than 16. For cases in which the renters’ quartiles or the owners’ quartiles (figures from Table 1) of a CSD are suppressed the CSD is assigned to a quartile range depending on the provincial renters’ or owners’ quartile figures. Number of Bedrooms (Unit Size) (6) 1. Total – Private households by number of bedrooms1 2. 0 bedrooms (Bachelor/Studio) 3. 1 bedroom 4. 2 bedrooms 5. 3 bedrooms 6. 4 bedrooms Note: 1) Dwellings with 5 bedrooms or more included in the total count only. Housing Suitability (6) 1. Total - Housing suitability 2. Suitable 3. Not suitable 4. One bedroom shortfall 5. Two bedroom shortfall 6. Three or more bedroom shortfall Note: 1) 'Housing suitability' refers to whether a private household is living in suitable accommodations according to the National Occupancy Standard (NOS); that is, whether the dwelling has enough bedrooms for the size and composition of the household. A household is deemed to be living in suitable accommodations if its dwelling has enough bedrooms, as calculated using the NOS. 'Housing suitability' assesses the required number of bedrooms for a household based on the age, sex, and relationships among household members. An alternative variable, 'persons per room,' considers all rooms in a private dwelling and the number of household members. Housing suitability and the National Occupancy Standard (NOS) on which it is based were developed by Canada Mortgage and Housing Corporation (CMHC) through consultations with provincial housing agencies. Shelter-cost-to-income-ratio (4) 1. Total – Private non-band non-farm off-reserve households with an income greater than zero 2. Spending less than 30% of households total income on shelter costs 3. Spending 30% or more of households total income on shelter costs 4. Spending 50% or more of households total income on shelter costs Note: 'Shelter-cost-to-income...

Conferences are an essential tool for scientific communication. In disciplines such as Computer Science, over 50% of original research results are published in conference proceedings. In this dataset, there is is a list of conference proceedings, categorized Q1 - Q4 by analogy with SJR journal quartiles. We have analyzed the role of conference proceedings in various disciplines and propose an alternative approach to research evaluation based on conference proceedings and Scimago Journal Rank (SJR). Comparison of the resulting list in Computer Science with the CORE ranking showed a 62% match, as well as an average rank correlation of the distribution by category.

This dataset contains gender pay gap figures for all employees in London and large employers in London. The pay gap figures for GLA group organisations can be found on their respective websites. The gender pay gap is the difference in the average hourly wage of all men and women across a workforce. If women do more of the less well paid jobs within an organisation than men, the gender pay gap is usually bigger. The UK government publish gender pay gap figures for all employers with 250 or more employees. A cut of this dataset that only shows employers that are registered in London can be found below. Read a report by the Local Government Association (LGA) that summarises the mean and median pay gaps in local authorities, as well as the distribution of staff across pay quartiles. This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more. This dataset is one of the Greater London Authority's measures of Economic Development strategy. Click here to find out more.

Affordability ratios calculated by dividing house prices by gross annual workplace-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

This dataset includes one dataset which was custom ordered from Statistics Canada.The table includes information on housing suitability and shelter-cost-to-income ratio by number of bedrooms, housing tenure, age of primary household maintainer, household type, and income quartile ranges for census subdivisions in British Columbia. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and variables: Geography: Non-reserve CSDs in British Columbia - 299 geographies The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. Housing Tenure Including Presence of Mortgage (5) 1. Total – Private non-band non-farm off-reserve households with an income greater than zero by housing tenure 2. Households who own 3. With a mortgage1 4. Without a mortgage 5. Households who rent Notes: 1) Presence of mortgage - Refers to whether the owner households reported mortgage or loan payments for their dwelling. 2015 Before-tax Household Income Quartile Ranges (5) 1. Total – Private households by quartile ranges1, 2, 3 2. Count of households under or at quartile 1 3. Count of households between quartile 1 and quartile 2 (median) (including at quartile 2) 4. Count of households between quartile 2 (median) and quartile 3 (including at quartile 3) 5. Count of households over quartile 3 Notes: 1) A private household will be assigned to a quartile range depending on its CSD-level location and depending on its tenure (owned and rented). Quartile ranges for owned households in a specific CSD are delimited by the 2015 before-tax income quartiles of owned households with an income greater than zero and residing in non-farm off-reserve dwellings in that CSD. Quartile ranges for rented households in a specific CSD are delimited by the 2015 before-tax income quartiles of rented households with an income greater than zero and residing in non-farm off-reserve dwellings in that CSD. 2) For the income quartiles dollar values (the delimiters) please refer to Table 1. 3) Quartiles 1 to 3 are suppressed if the number of actual records used in the calculation (not rounded or weighted) is less than 16. For cases in which the renters’ quartiles or the owners’ quartiles (figures from Table 1) of a CSD are suppressed the CSD is assigned to a quartile range depending on the provincial renters’ or owners’ quartile figures. Number of Bedrooms (Unit Size) (6) 1. Total – Private households by number of bedrooms1 2. 0 bedrooms (Bachelor/Studio) 3. 1 bedroom 4. 2 bedrooms 5. 3 bedrooms 6. 4 bedrooms Note: 1) Dwellings with 5 bedrooms or more included in the total count only. Housing Suitability (6) 1. Total - Housing suitability 2. Suitable 3. Not suitable 4. One bedroom shortfall 5. Two bedroom shortfall 6. Three or more bedroom shortfall Note: 1) 'Housing suitability' refers to whether a private household is living in suitable accommodations according to the National Occupancy Standard (NOS); that is, whether the dwelling has enough bedrooms for the size and composition of the household. A household is deemed to be living in suitable accommodations if its dwelling has enough bedrooms, as calculated using the NOS. 'Housing suitability' assesses the required number of bedrooms for a household based on the age, sex, and relationships among household members. An alternative variable, 'persons per room,' considers all rooms in a private dwelling and the number of household members. Housing suitability and the National Occupancy Standard (NOS) on which it is based were developed by Canada Mortgage and Housing Corporation (CMHC) through consultations with provincial housing agencies. Shelter-cost-to-income-ratio (4) 1. Total – Private non-band non-farm off-reserve households with an income greater than zero 2. Spending less than 30% of households total income on shelter costs 3. Spending 30% or more of households total income on shelter costs 4. Spending 50% or more of households total income on shelter costs Note: 'Shelter-cost-to-income ratio' refers to the proportion of average total income of household which is spent on shelter costs. Household Statistics (8) 1....

Affordability ratios calculated by dividing house prices by gross annual residence-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

Community-based HIV testing offers an alternative approach to encourage HIV testing among men in sub-Saharan Africa. In this study, we evaluated a community-based HIV testing strategy targeting male bar patrons in northern Tanzania to assess factors predictive of prior HIV testing and factors predictive of accepting a real-time HIV test offer. Participants completed a detailed survey and were offered HIV testing upon survey completion. Poisson regression was used to identify prevalence ratios for the association between potential predictors and prior HIV testing or real-time testing uptake. Of 359 participants analyzed, the median age was 41 (range 19–82) years, 257 (71.6%) reported a previous HIV test, and 321 (89.4%) accepted the real-time testing offer. Factors associated with previous testing for HIV (adjusted prevalence ratio [aPR], 95% CI) were wealth scores in the upper-middle quartile (1.25, 1.03–1.52) or upper quartile (1.35, 1.12–1.62) and HIV knowledge (1.04, 1.01–1.07). Factors that predicted real-time testing uptake were lower scores on the Gender-Equitable Men scale (0.99, 0.98–0.99), never testing for HIV (1.16, 1.03–1.31), and testing for HIV > 12 months prior (1.18, 1.06–1.31). We show that individual-level factors that influence the testing-seeking behaviors of men are not likely to impact their acceptance of an HIV offer.

Dataset contains patient identification from 1 to 82 (ID), steatosis grade (Steatosis), inflammation grade (Inflammation), fibrosis stage (Fibrosis), point shear wave elasticity (pSWE), μn = mean intensity normalized by its maximal value (munMean), 1/α = reciprocal of the scatterer clustering parameter (ialphaMean), k = coherent-to-diffuse signal ratio (kMean), 1/(k + 1) = diffuse-to-total signal power ratio (ikappaMean), mean intensity normalized by its maximal value inter-quartile range (munIQR), reciprocal of the scatterer clustering parameter inter-quartile range (ialphaIQR), coherent-to-diffuse signal ratio inter-quartile range (kIQR), diffuse-to-total signal power ratio inter-quartile range (ikappaIQR),total attenuation coefficient slope (TotalACS), local attenuation coefficient slope (LocalACS). (XLSX)